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Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media

Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media

Hadj Ahmed Bouarara
Copyright: © 2021 |Volume: 12 |Issue: 2 |Pages: 15
ISSN: 1941-868X|EISSN: 1941-8698|EISBN13: 9781799860310|DOI: 10.4018/IJISSC.2021040101
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MLA

Bouarara, Hadj Ahmed. "Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media." IJISSC vol.12, no.2 2021: pp.1-15. http://doi.org/10.4018/IJISSC.2021040101

APA

Bouarara, H. A. (2021). Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media. International Journal of Information Systems and Social Change (IJISSC), 12(2), 1-15. http://doi.org/10.4018/IJISSC.2021040101

Chicago

Bouarara, Hadj Ahmed. "Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media," International Journal of Information Systems and Social Change (IJISSC) 12, no.2: 1-15. http://doi.org/10.4018/IJISSC.2021040101

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Abstract

A recent British study of people between the ages of 14 and 35 has shown that social media has a negative impact on mental health. The purpose of the paper is to detect people with mental disorders' behavior in social media in order to help Twitter users in overcoming their mental health problems such as anxiety, phobia, depression, paranoia, etc. For this, the author used text mining and machine learning algorithms (naïve Bayes, k-nearest neighbours) to analyse tweets. The obtained results were validated using different evaluation measures such as f-measure, recall, precision, entropy, etc.

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